Abstract: Alcohol use during adolescence and young adulthood remains a critical area for research, which is well-recognized by the National Institute on Alcohol Abuse and Alcoholism's (NIAAA) Underage Drinking Research Initiative and the report from the Task Force of the National Advisory Council on Alcohol Abuse and Alcoholism (2002). Alcohol use and its negative consequences are a significant public health concern given the biological, social, and environmental effects they exert on individuals and society. It is important to better understand the variable patterns of alcohol use that individuals exhibit over time (e.g., consistently low alcohol use, rapidly increasing alcohol use) during this key developmental period. Growth mixture modeling (GMM) is a statistical technique that is used to identify latent subgroups of individuals who exhibit distinct patterns of alcohol use over time. Despite the widespread use of GMM, a limited number of studies have examined how study design factors may affect alcohol use trajectories used to identify latent subgroups in GMM. The proposed research focuses specifically on the effect of measurement timing (i.e., number and spacing of assessments) in longitudinal studies. Decision-making about how to space assessments is particularly challenging in the context of GMM, because the hypothesized latent subgroups may exhibit different trends in alcohol use over time based on design features rather than actual changes. This project proposes to investigate how measurement timing affects the shape of individuals' alcohol use trajectories in the context of GMM. The specific aims are to: (1) conduct a Monte Carlo simulation study that evaluates how the number and spacing of assessments affects the alcohol use trajectories used to identify latent alcohol use subgroups in GMM; (2) provide an application of GMM using alcohol data from the National Longitudinal Survey of Youth 1997 that demonstrates the extent to which the number and spacing of assessments affects the alcohol use trajectories used to identify the latent subgroups; and (3) communicate the findings to both quantitative and applied researchers and suggest specific considerations for designing longitudinal GMM studies. The main implication of the proposed research is to aid applied researchers in designing GMM studies that adequately measure the patterns of alcohol use that individuals exhibit over time. Researchers may then conduct more fine-grained examinations of etiological predictors of and distal outcomes associated with the latent class trajectories. These and subsequent findings may also facilitate identification of individuals for prevention or intervention programs based on information about the predictors of particular alcohol use trajectories. PUBLIC HEALTH RELEVANCE: Project Narrative: The proposed research seeks to enhance our knowledge of how to best measure individuals' patterns of alcohol use during adolescence and young adulthood, which is a key period for the development of alcohol- related behaviors. As indicated in the Surgeon General's report (U.S. Department of Health and Human Services, 2007), it is important to understand individuals' patterns of alcohol use over time given the implications such understanding has for tailoring prevention and intervention programs to individuals who exhibit particular patterns of alcohol use.